1. Field of the Invention
The present invention relates generally to inventory allocation and, more particularly, to a system having an inventory allocation tool and method of using same.
2. Description of the Related Art
It is known that a large retailer typically has a number of retail stores with distribution centers located near groups of retail stores to supply inventory to the retail stores. For a large retailer, the collection of distribution centers may be referred to as a distribution network. Vendors typically supply the large retailer with items that are kept in inventory at the distribution centers, which subsequently distribute the items to the retail stores. In that regard, most vendors ship a number of the same items in a pack or vendor pack size and require the retailer to order a minimum quantity of the items at any one time. However, both the minimum order quantity and vendor pack size can vary by items and vendors, which constraints are imposed by vendors and are not constraints imposed by the retailer. A minimum order quantity (MOQ) is the least number of items that can be ordered from a vendor to get shipped to a specific distribution center. Since items shipped for a vendor come in packages, the number of items requested from a vendor must be a multiple of the vendor pack size.
To be efficient, a larger retailer may have an allocation policy for an inventory item for a given must arrive by date (MABD), which consists of a list of distribution centers and allocation percentages associated with each of them. When a Merchandise Planner team or automated replenishment system in the large retailer decides to order a quantity of an item for the specific MABD for the whole distribution network based on weeks of supply, inventory build up strategy for holidays or peaks or promotion offers, the order quantity of items gets distributed among the specific distribution centers in the distribution network so that it follows the allocation policy and vendor constraints (e.g., vendor pack size and minimum order quantity).
It is also known to provide an Inventory Allocation Tool (IAT) for a large retailer that takes into account the allocation policy, order quantity, minimum order quantity, and vendor pack size as inputs, and distributes the order quantity among the specific distribution centers recommended by the allocation policy so that the minimum order quantity and vendor pack size is respected as the IAT tries to follow the allocation percentages suggested by the allocation policy. The IAT is the last step of inventory allocation for the large retailer and its importance comes from the fact that the IAT produces an executable purchase order for each specific distribution center. Each specific distribution center takes the executable purchase order and orders the number of items from the vendor, who ships the items to the specific distribution center.
One disadvantage of the above-described IAT is that the IAT sometimes over orders items to satisfy vendor pack size constraints. For example, suppose the Merchandise Planner team would like to buy twenty (20) units of item A from a vendor which has a minimum order quantity of five (5) and a vendor pack size of five (5). Assuming the allocation policy is recommending three distribution centers (D1, D2, D3) with allocation percentages (30%, 40%, 30%), respectively, there should ideally be (6, 8, 6) units in the distribution centers (D1, D2, D3), respectively. However, the IAT over buys and produces purchase orders of size (10, 10, 10) for the distribution centers (D1, D2, D3), respectively, to satisfy the allocation policy based on the vendor constraints. This results in more cost being imposed on the large retailer to order a quantity of an item greater than its sale forecast and also since each distribution center has limited storage capacity, having the extra volume of an item, will impact other items which need to be in the same distribution center.
Another disadvantage of the above-described IAT is that the IAT creates significant deviation from the allocation policy while trying to satisfy the minimum order quantity. This can get translated to allocating an item completely different from the allocation policy. For example, an item could end up in only one distribution center on the east coast when there are demands on the west cost or vice versa, which is extremely against the allocation policy which recommends distributing an item in both distribution centers. For example, suppose the Merchandise Planner team would like to buy twenty (20) units of an item A from a vendor which has a minimum order quantity of ten (10) and vendor pack size of two (2). Assuming the allocation policy is recommending two distribution centers (D1, D2) with an allocation percentage (40%, 60%), respectively, there should ideally be (8, 12) units in the distribution centers (D1, D2), respectively. The IAT produces purchase orders of size (0, 20) for the distribution centers (D1, D2), respectively. This potentially causes cross country shipping for the large retailer, which increases the cost of shipping and time of transit for the items.
It is, therefore, desirable to provide a new IAT which distributes an order quantity among distribution centers so that vendor constraints (e.g., minimum order quantity and vendor pack size) are respected. It is also desirable to provide a new IAT that does not over order items and brings the distribution of the order quantity closest to the distribution recommended by the allocation policy. It is further desirable to provide a new IAT that does not significantly deviate from the allocation policy. Thus, there is a need in the art to provide a system having a new IAT and method of using same that meets at least one of these desires.